We present a novel application of WordNet to estimating the interestingness of rules discovered by data-mining methods. We estimate the novelty of text-mined rules using semantic distance measures based on WordNet. In our experiments, we found that the automatic scoring of rules based on our novelty measure correlates with human judgments about as well as human judgments correlate with each other.